This study aimed at exploring the impact of post-epidemic era on teachers’ behavioral intention of distance education. In this study, purposive sampling method was used to enroll 390 teachers in colleges and universities, high schools and vocational schools, and junior high and elementary schools to be the research subjects for the questionnaire survey. A total of 360 questionnaires were collected for statistics, and AMOS 23.0 statistical software was used to analyze the correlation between variables. Meanwhile, a structural equation model was used to analyze and verify the impact of the technology acceptance model, information system success model, and diffusion of innovations theory. According to the results, the system quality of distance teaching platforms certainly affected perceived usefulness, and perceived usefulness affected teachers’ attitudes toward using distance teaching systems. In addition, perceived ease of use had an impact on perceived usefulness, and trialability had an impact on teachers’ attitudes toward using distance teaching systems. Finally, teachers’ attitude toward using a distance teaching system also affected their behavioral intention. According to the results, suggestions were made in this study to teachers and students for distance teaching. Additionally, the main contribution of this study lies in providing specific strategies for further distance teaching through empirical results in combination with on-site teaching.

Over the last few decades, the training methods for rowers have been converging toward similar models owing to the progress in science and technology, in particular, the increased flow of information. As a result, rowing performance in competitions at the international level is the best it has ever been. However, it is possible to further enhance rowers’ performance. An important first step to obtain an advantage on the race course is the selection of rowing athletes. The selection method presented here began by inviting experts and scholars in the field to complete a questionnaire, which was established through the analysis and compilation of relevant literature on rowing and athlete selection. Subsequently, the modified Delphi method is applied to achieve an expert consensus on the selection criteria to be evaluated. Five primary criteria, including athlete monitoring via internet-of-things (IoT) technology, and twenty sub-criteria were identified for the selection of elite rowers. An evaluation model for the athletes was constructed from the data using the analytic hierarchy process. The results showed that when selecting rowers the primary criterion of body factor has the highest priority, followed by IoT measurement factor, professional factor, reaction factor, and psychological factor. Furthermore, it reveals that the important sub-criteria affecting athlete selection are body composition, muscle composition, and competition scores. The framework provided by this study for the selection of elite rowers can be refined and adapted for the selection of elite athletes in related sports.

The recent COVID-19 epidemic has affected the global sports industry to a certain extent, and health clubs are no exception. To avoid unsustainable operations, health clubs need to restructure their programs to suit members’ needs. Therefore, this study constructs a two-stage framework model to evaluate health club members’ purchase of coaching programs. The first stage is to construct a hierarchy of evaluation, using the modified Delphi method, to select suitable criteria and extended sub-criteria, and add and delete them through expert discussion. In the second stage, we use the pairwise comparison matrix to calculate the weight of each criterion and sub-criterion to influence each other. Next, we evaluate and compare physical, online and offline, and live-stream coaching programs, by using network hierarchy analysis to identify the best class purchase plan during the epidemic and provide relevant suggestions. The results of the study found that during the epidemic, the primary sales were for weight training among physical programs (0.314), and activity classes among online and offline programs (0.633) as well as live-stream coaching programs (0.280). These findings have implications for health clubs in deciding which mode they need to adopt for sustainable operations.

Recently, augmented reality (AR) games have gained popularity as consumers' acceptance for AR games as a new lifestyle is rising. In this study, we use the gray relational analysis method to construct players to evaluate the factors and order of downloading AR games. Finally, Poke.mon GO, Pet City, and My Hero GO, three different AR games, were evaluated for player download factors to provide game developers with reference indicators for developing real-life games.